Abstract
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Correlation between the five personality types and the popularity of music
Heatmap chart
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Introduction
Our investigation into the link between personality and choice of mainstream music transcends mere curiosity as its is a question that subtly influences us on a daily basis.
Prevailing stereotypes dictate that the average mainstream music enjoyer embody certain characteristics such as extraversion whereas those who are entrenched in niche musical subcultures are perceived differently (more open for example), leading us to make assumptions regarding those around us. While this is a common bias, it is also one that we see be disproven time and time again. Why then do these stereotypes live on? Could it be that there is a validity to linking traits such as extreme extraversion with affinity towards popular music or are there other qualities such as agreeableness that predict this affinity better?
This plays an even bigger role when we take into consideration the social aspect of music and how it is a tool to connect people. Regardless of where one falls on the OCEAN (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) scale, your preferences may align with someone who seemingly falls on the opposite side. Thus making the closer examination of the intersection between personality and popularity even more intriguing.
Chart explanation / our findings
Methodology
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BIG METHODOLOGY CHART
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General methodology background
The Intersection of personality & music listening is one that has been heavily studied by several researchers with focus being placed on the relationship between preferences for musical attributes and personality (Greenberg, Kosinski et al. 2016) or music listening behavior on Spotify and personality (Anderson, Gil, Greenberg, 2020) for example.
This fascination with music’s inherent interplay with personality is what lead us to our research question: Is personality a significant predictor of whether someone listens to mainstream or non mainstream music? In our case personality being measured using a shortened version of the big five inventory - the TiPi test.
We decided that this instrument for personality measurement was best suited for our study due to its accessibility (as people are more likely to finish a shorter questionnaire) and efficiency. Additionally the metrics of Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism are ones that have cross-cultural applicability, standardized scoring and interpretation, and are widely accepted comprehensive frameworks.
Additionally popularity was chosen as the track feature we will be measuring personality against, as it sheds light on inclinations towards music that align with prevailing trends or deviate to more niche choices thus adding our own particular angle on the wider lens of personality and music taste.
We will be using Spotify, specifically the Spotify “On Repeat” Playlist data of participants in order to analyze their music listening data as this playlist represents tracks that are most up to date with the participants listening repertoire.
Our study hopes to ultimately culminate in a deeper understanding of how individual psychological characteristics influence music preferences and contribute to the ever evolving conversation regarding the relationship between music and personality
Tipi questions
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embedded spotify playlist
Openness
OPENNESS
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Correlation chart
Distribution
Description
description of the charts
Conscientiousness
CONSCIENTIOUSNESS
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Correlation chart
Distribution
Description
description of the charts
Extraversion
EXTRAVERSION
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Correlation chart
Distribution
Description
description of the charts
Agreeableness
AGREEABLENESS
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Correlation chart
Distribution
Description
description of the charts
Neuroticism
NEUROTICISM
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Correlation chart
Distribution
Description
description of the charts
Evaluation/Reflection
Evaluation/Reflection
Background
Article reviews
Music Recommender systems
Music recommender systems are an integral part of modern-day music listening. They are adopted by streaming services such as Spotify and Apple Music and are part of their core feature set. These recommender systems, however, are not perfect. One of the issues described in “Support the underground: characteristics of beyond-mainstream music listeners” by Kowald et al. (2021) is the popularity bias these recommender systems have: popular songs are over-represented in recommendation lists. Furthermore, a study by Tintarev et al. (2013) found that openness to new music and the diversity of music within a group influences recommendation quality. The authors set to find out what the characteristics of beyond-mainstream music tracks and music listeners are, and how these characteristics correlate with openness and diversity patterns as well as with recommendation quality.
The authors of the article aimed to identify the characteristics of beyond-mainstream music tracks and listeners and how these characteristics influence recommendation quality in addition to openness and diversity patterns. The authors observed that beyond-mainstream music listeners receive worse recommendations, except for a certain subgroup with a high openness value. This subgroup received even better recommendations than mainstream music listeners.